Digital predistortion for compensation of nonlinearities in Radio over Fiber Links

In order to cope up with the ever increasing demand for larger transmission bandwidth, Radio over Fiber technology is a very beneficial solution. These systems are expected to play a major role within future fifth generation wireless networks due to their inherent capillary distribution properties. Nonlinear compensation techniques are becoming increasingly important to improve the performance of telecommunication channels by compensating for channel nonlinearities. Indeed, significant bounds on the technology usability and performance degradation occur due to nonlinear characteristics of optical transmitter, nonlinear generation of spurious frequencies, which, in the case of RoF links exploiting Directly Modulated Lasers , has the combined effect of laser chirp and optical fiber dispersion among its prevailing causes. The purpose of the research is to analyze some of the main causes of harmonic and intermodulation distortion present in Radio over Fiber (RoF) links, and to suggest a solution to reduce their effects, through a digital predistortion technique. Predistortion is an effective and interesting solution to linearize and this allows to demonstrate that the laser’s chirp and the optical fiber’s dispersion are the main causes which generate harmonic distortion. The improvements illustrated are only theoretical, based on a feasibility point of view. The simulations performed lead to significant improvements for short and long distances of radio over fiber link lengths. The algorithm utilized for simulation has been implemented on MATLAB. The effects of chirp and fiber nonlinearity in a directly modulated fiber transmission system are investigated by simulation, and a cost effective and rather simple technique for compensating these effects is discussed. A detailed description of its functional model is given, and its attractive features both in terms of quality improvement of the received signal, and cost effectiveness of the system are illustrated.

Performance analysis of different sensing techniques in Cognitive Radio Networks.

The spectrum of radiofrequency is distributed in such a way that it is fixed to certain users called licensed users and it cannot be used by unlicensed users even though the spectrum is not in use. This inefficient use of spectrum leads to spectral holes. To overcome the problem of spectral holes and increase the efficiency of the spectrum, Cognitive Radio (CR) was used and all simulation work was done on MATLAB. Here analyzed the performance of different spectrum sensing techniques as Match filter based spectrum sensing and energy detection, which depend on various factors, systems such as Numbers of input, signal-to-noise ratio ( SNR Ratio), QPSK system and BPSK system, and different fading channels, to identify the best possible channels and systems for spectrum sensing and improving the probability of detection. The study resulted that an averaging filter being better than an IIR filter. As the number of inputs and SNR increased, the probability of detection also improved. The Rayleigh fading channel has a better performance compared to the Rician and Nakagami fading channel.

Exploration of X-ray, optical and radio emission of the radio-galaxy 3C 277.3

This thesis explores the X-ray nuclear and extended properties of the radio galaxy 3C 277.3, where a recent optical observation performed with the multi-unit spectroscopic explorer (MUSE) has revealed star-forming regions triggered by the propagation of non-thermal plasma in the intergalactic medium. This work aims to study the nuclear engine and its environment and, possibly, discover signatures of non-thermal plasma-gas interaction at high energies. 3C 277.3 was observed with the Chandra satellite five times from 2010 to 2014 for a total of about 200 ks. Data in the Chandra public archive were retrieved and analyzed. When necessary, the different pointings were combined to improve the signal-to-noise ratio. A detailed analysis of the Chandra image (obtained by combining all the observations) has revealed several emission regions. In addition to a bright nucleus, two jet knots and the northern hot spot were clearly detected by overlapping the X-ray data to a VLA map of the source at 1.4 GHz. An X-ray spectral analysis was performed for all these structures. Finally, the X-ray image was over-imposed on the MUSE data.

Image Processing Algorithms applied to Radio SLAM using MIMO Radars

Radio Simultaneous Location and Mapping (SLAM) consists of the simultaneous tracking of the target and estimation of the surrounding environment, to build a map and estimate the target movements within it. It is an increasingly exploited technique for automotive applications, in order to improve the localization of obstacles and the target relative movement with respect to them, for emergency situations, for example when it is necessary to explore (with a drone or a robot) environments with a limited visibility, or for personal radar applications, thanks to its versatility and cheapness. Until today, these systems were based on light detection and ranging (lidar) or visual cameras, high-accuracy and expensive approaches that are limited to specific environments and weather conditions. Instead, in case of smoke, fog or simply darkness, radar-based systems can operate exactly in the same way. In this thesis activity, the Fourier-Mellin algorithm is analyzed and implemented, to verify the applicability to Radio SLAM, in which the radar frames can be treated as images and the radar motion between consecutive frames can be covered with registration. Furthermore, a simplified version of that algorithm is proposed, in order to solve the problems of the Fourier-Mellin algorithm when working with real radar images and improve the performance. The INRAS RBK2, a MIMO 2x16 mmWave radar, is used for experimental acquisitions, consisting of multiple tests performed in Lab-E of the Cesena Campus, University of Bologna. The different performances of Fourier-Mellin and its simplified version are compared also with the MatchScan algorithm, a classic algorithm for SLAM systems.